GPT-4.1 nano
Multimodal
Zero-eval
#2OpenAI-MRCR: 2 needle 1M
#3Graphwalks parents >128k
#3Graphwalks BFS >128k
by OpenAI
About
GPT-4.1 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 25 benchmarks. It excels particularly in MMLU (80.1%), IFEval (74.5%), CharXiv-D (73.9%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents OpenAI's latest advancement in AI technology.
Pricing Range
Input (per 1M)$0.10 -$0.10
Output (per 1M)$0.40 -$0.40
Providers1
Timeline
AnnouncedApr 14, 2025
ReleasedApr 14, 2025
Knowledge CutoffMay 31, 2024
Specifications
Capabilities
Multimodal
License & Family
License
Proprietary
Benchmark Performance Overview
Performance metrics and category breakdown
Overall Performance
25 benchmarks
Average Score
36.1%
Best Score
80.1%
High Performers (80%+)
1Performance Metrics
Max Context Window
1.1MAvg Throughput
200.0 tok/sAvg Latency
2msTop Categories
code
74.5%
math
56.2%
vision
55.4%
long_context
48.3%
general
32.4%
Benchmark Performance
Top benchmark scores with normalized values (0-100%)
Ranking Across Benchmarks
Position relative to other models on each benchmark
MMLU
Rank #45 of 78
#42Llama 3.1 Nemotron 70B Instruct
80.2%
#43DeepSeek-V2.5
80.4%
#44Nova Lite
80.5%
#45GPT-4.1 nano
80.1%
#46Qwen2.5 14B Instruct
79.7%
#47Llama 4 Scout
79.6%
#48Claude 3 Sonnet
79.0%
IFEval
Rank #33 of 37
#30Granite 3.3 8B Base
74.8%
#31Granite 3.3 8B Instruct
74.8%
#32Llama 3.2 3B Instruct
77.4%
#33GPT-4.1 nano
74.5%
#34Qwen2.5 7B Instruct
71.2%
#35IBM Granite 4.0 Tiny Preview
63.0%
#36Phi 4
63.0%
CharXiv-D
Rank #5 of 5
#2GPT-4o
85.3%
#3GPT-4.1
87.9%
#4GPT-4.1 mini
88.4%
#5GPT-4.1 nano
73.9%
MMMLU
Rank #12 of 13
#9Phi-3.5-MoE-instruct
69.9%
#10GPT-4.1 mini
78.5%
#11GPT-4o
81.4%
#12GPT-4.1 nano
66.9%
#13Phi-3.5-mini-instruct
55.4%
OpenAI-MRCR: 2 needle 1M
Rank #2 of 3
#1GPT-4.1
61.2%
#2GPT-4.1 nano
59.9%
#3GPT-4.1 mini
23.5%
All Benchmark Results for GPT-4.1 nano
Complete list of benchmark scores with detailed information
MMLU MMLU benchmark | general | text | 0.80 | 80.1% | Self-reported |
IFEval IFEval benchmark | code | text | 0.74 | 74.5% | Self-reported |
CharXiv-D CharXiv-D benchmark | general | text | 0.74 | 73.9% | Self-reported |
MMMLU MMMLU benchmark | general | text | 0.67 | 66.9% | Self-reported |
OpenAI-MRCR: 2 needle 1M OpenAI-MRCR: 2 needle 1M benchmark | long_context | text | 0.60 | 59.9% | Self-reported |
Multi-IF Multi-IF benchmark | general | text | 0.57 | 57.2% | Self-reported |
MathVista MathVista benchmark | math | text | 0.56 | 56.2% | Self-reported |
MMMU MMMU benchmark | vision | multimodal | 0.55 | 55.4% | Self-reported |
GPQA GPQA benchmark | general | text | 0.50 | 50.3% | Self-reported |
COLLIE COLLIE benchmark | general | text | 0.42 | 42.5% | Self-reported |
Showing 1 to 10 of 25 benchmarks
Resources